CVE-2025-27528

Comprehensive Technical Analysis of CVE-2025-27528

1. Vulnerability Assessment and Severity Evaluation

CVE ID: CVE-2025-27528 CVSS Score: 9.1

The vulnerability in question is a Deserialization of Untrusted Data issue affecting Apache InLong, a data integration framework. Deserialization vulnerabilities are particularly severe because they can allow attackers to execute arbitrary code or manipulate the application's logic. The CVSS score of 9.1 indicates a critical severity level, highlighting the potential for significant impact if exploited.

2. Potential Attack Vectors and Exploitation Methods

Attack Vectors:

• Network-Based Attacks: An attacker could send specially crafted data to the InLong JDBC component, which, upon deserialization, could lead to arbitrary file reading.
• Man-in-the-Middle (MitM) Attacks: If an attacker can intercept and modify data in transit, they could inject malicious serialized data.
• Insider Threats: Malicious insiders with access to the system could exploit this vulnerability to read sensitive files.

Exploitation Methods:

• Crafting Malicious Payloads: Attackers can create serialized objects that, when deserialized, perform unauthorized actions such as reading arbitrary files.
• Exploiting Trust Boundaries: By exploiting the trust boundaries within the application, attackers can bypass security mechanisms and gain unauthorized access to sensitive data.

3. Affected Systems and Software Versions

Affected Versions:

• Apache InLong versions from 1.13.0 through 2.1.0 are affected by this vulnerability.

Unaffected Versions:

• Apache InLong version 2.2.0 and later are not affected, as the vulnerability has been patched in these versions.

4. Recommended Mitigation Strategies

Immediate Actions:

• Upgrade: Users are strongly advised to upgrade to Apache InLong version 2.2.0 or later.
• Patch: For users who cannot upgrade immediately, cherry-picking the fix from the provided GitHub pull request (#11747) is recommended.

Long-Term Strategies:

• Input Validation: Implement robust input validation to ensure that only trusted data is deserialized.
• Access Controls: Enforce strict access controls to limit the exposure of sensitive data.
• Network Security: Use secure communication protocols (e.g., TLS) to protect data in transit.
• Monitoring and Logging: Enhance monitoring and logging to detect and respond to suspicious activities promptly.

5. Impact on Cybersecurity Landscape

Deserialization vulnerabilities are a recurring issue in the cybersecurity landscape, particularly in applications that handle serialized data. This vulnerability underscores the importance of secure coding practices and the need for continuous monitoring and updating of software dependencies. The high CVSS score indicates that organizations must prioritize addressing such vulnerabilities to prevent potential data breaches and unauthorized access.

6. Technical Details for Security Professionals

Technical Overview:

• Deserialization Process: The vulnerability arises from the deserialization of untrusted data in the InLong JDBC component. Deserialization converts serialized data back into an object, which can be manipulated to perform unauthorized actions.
• Security Mechanisms Bypass: The flaw allows attackers to bypass existing security mechanisms, leading to arbitrary file reading. This can result in the exposure of sensitive information, including configuration files, credentials, and other critical data.

Mitigation Steps:

1. Upgrade to Version 2.2.0: Ensure that all instances of Apache InLong are upgraded to version 2.2.0 or later.
2. Cherry-Pick Fix: If upgrading is not feasible, apply the fix from the GitHub pull request #11747.
3. Implement Input Validation: Ensure that all serialized data is validated before deserialization.
4. Enhance Access Controls: Review and strengthen access controls to limit the exposure of sensitive data.
5. Use Secure Communication Protocols: Ensure that data in transit is protected using secure communication protocols.
6. Monitor and Log: Implement comprehensive monitoring and logging to detect and respond to suspicious activities.

References:

• GitHub Pull Request #11747
• Apache Mailing List
• Openwall Mailing List

By following these recommendations, organizations can effectively mitigate the risks associated with CVE-2025-27528 and enhance their overall cybersecurity posture.